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11-17-2016 10:07 PM

Dear all,

I used **proc phreg** to run **fine and gray** model. My dataset has no missing value, and when the univeriate analysis was taken, everything is OK (the number of used observations = the number of read observations). But when the multivariate model was analized, things would be like this, the log as below:

ods graphics on;

proc phreg data=model_os_m plots(overlay=stratum)=cif;

class A (ref='Normal');

class B(order=internal ref=first) C(order=internal ref=first);

model dftime*status(0)=A B C D / eventcode=1;

Hazardratio 'Pairwise' A / diff=pairwise;

baseline covariates=cov_os2_m out=outos2m cif=_all_;

run;

**NOTE: 331 observations were deleted due either to missing or invalid values for the time,****censoring, frequency or explanatory variables or to invalid operations in generating the****values for some of the explanatory variables.**

NOTE: Convergence criterion (GCONV=1E-8) satisfied.

I have tried proc print/frequency in the Fine and gray model, but the log states that NOTE: The RESMART= option (OUTPUT statement) is ignored for the Fine and Gray competing-risks analysis.

So, why 331 observations have been deleted in the multivariate analysis? And how can I identify which observations have not been used in the final model? Could you please tell me how can I solve this problem in fine and gray model test?

Thank you very much!

Alddle

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Solution

11-23-2016
08:16 AM

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11-23-2016 08:14 AM

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11-18-2016 12:43 AM

It does say invalid values. Do all your times make sense?

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11-18-2016 01:20 AM

Dear Reeza,

Thanks. Do you mean tied event times? Or you mean the robust covariance matrix? But, why univeriate analysis of each factor for fine and fray model is OK? Could you please tell me how can I find these invalid times?

Best,

Alddle

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11-18-2016 01:32 AM - edited 11-18-2016 01:40 AM

I have checked the dftimes, and found that only 61 pairs of observation have tied event times.

Solution

11-23-2016
08:16 AM

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11-23-2016 08:14 AM